A method for parameter extraction and channel state prediction in mobile-to-mobile wireless channels

This paper investigates the prediction of single input single output (SISO) narrowband multipath fading channels for mobile-to-mobile wireless communications. Using a statistical model for mobile to mobile urban and suburban channels, we derive a parametrized model and utilize the ESPRIT algorithm to extract the effective Doppler frequencies from noisy channel estimates. The parameter estimates are then used to forecast the mobile-to-mobile channel into the future. Using the Cramer Rao bound for function of parameters, a bound on the prediction error of M2M wireless channels is derived. Simulations were performed to evaluate the performance of the prediction scheme and comparison was made with the prediction of typical fixed to mobile channels and also with the derived bound. Results show that the performance of the scheme approaches the bound as the SNR increases.